Collaborative Research: Shedding Light on the Complex and Covariant Properties of Massive Halos with Theory and Observations

合作研究：通过理论和观测揭示大质量晕的复杂和协变特性

• 批准号: 2206695
• 负责人: Benedikt Diemer
• 金额: $ 34.53万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2206695&HistoricalAwards=false
• 关键词: Collaborative; Research; Shedding; Light; Complex

The most promising place to learn about the nature of dark matter is in the densest objects it forms, which are called "halos." As dark matter is invisible, however, it is challenging to infer even the simplest properties of halos, such as their total mass. We know of various observable indicators that (imperfectly) correlate with mass, including the stars of the galaxies in a halo, the bending of light around it, and the imprint of gas on background light from the early Universe. The difficulty has been to combine the information from these indicators because the different types of observations were typically available for different parts of the sky. With new, overlapping surveys, we can now combine different observables for the same halos. This observer-theorist collaboration between scientists at the University of Maryland, College Park and the University of California, Santa Cruz, will develop a framework to interpret combined observables based on some of the largest supercomputer simulations of the formation of halos and galaxies and on fast machine learning techniques. The team will apply this framework to a unique combination of survey data that they have access to. This project will also support Latinx STEM students at UC Santa Cruz via the newly created Seed Spoon Science program, which relies on the cultural practices of growing and cooking food to create a long-term mentoring community.The mass and density structure of cluster halos contain a wealth of cosmological and physical information, but they must be inferred from imperfect observational tracers such as the stars from central and satellite galaxies, the Sunayev-Zel’dovich signal from gas, and weak lensing. The new era of large, overlapping sky surveys now makes it possible to combine multi-wavelength observables for the same cluster halos, but to do so we need to understand their complex covariances. This project proposes to develop a theoretical and practical framework for interpreting panchromatic observations based on some of the largest simulations of structure formation, on flexible physical models, and on fast machine learning techniques. The team will apply this framework to the overlapping Dark Energy Spectroscopic Instrument (DESI), Atacama Cosmology Telescope (ACT), Dark Energy Camera Legacy Survey (DECaLS), and Hyper Suprime-Cam (HSC) footprints in order to observationally constrain the covariance of dark matter halo properties for galaxy clusters.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

了解暗物质本质最有希望的地方是它形成的致密物体，它们被称为“晕”。“然而，由于暗物质是不可见的，因此即使是推断晕的最简单属性，例如它们的总质量，也是具有挑战性的。我们知道各种可观测的指标与质量（不完全）相关，包括星系晕中的恒星，周围光线的弯曲，以及早期宇宙背景光上的气体印记。困难在于将这些指示器的信息联合收割机结合起来，因为不同类型的观测通常可用于天空的不同部分。有了新的、重叠的观测，我们现在可以联合收割机将不同的观测值结合起来，得到同一个晕。马里兰州大学帕克分校和加州大学圣克鲁斯分校的科学家之间的这项观察者-理论家合作，将开发一个框架，根据一些最大的超级计算机对光环和星系形成的模拟以及快速的机器来解释组合可观测量。学习技术。该小组将把这一框架应用于他们可以获得的独特的调查数据组合。该项目还将通过新创建的种子勺科学项目支持加州大学圣克鲁斯的拉丁裔STEM学生，该项目依赖于种植和烹饪食物的文化实践来创建长期的指导社区。星系团晕的质量和密度结构包含丰富的宇宙学和物理信息，但它们必须从不完善的观测示踪剂中推断出来，例如来自中央星系和卫星星系的恒星，来自气体的Sunayev-Zel'dovich信号和弱透镜。大规模重叠巡天的新时代，现在使得联合收割机将多波长观测数据结合起来用于同一个星团晕成为可能，但要做到这一点，我们需要了解它们复杂的协方差。该项目建议开发一个理论和实践框架，用于解释全色观测，其基础是一些最大的结构形成模拟，灵活的物理模型和快速机器学习技术。该团队将把这个框架应用于重叠的暗能量光谱仪器（DESI）、阿塔卡马宇宙学望远镜（ACT）、暗能量相机遗产调查（DECaLS）、Hyper Suprime-Cam（HSC）该奖项反映了NSF的法定使命，并已被认为是值得支持的，通过评估使用基金会的知识价值和更广泛的影响审查标准。